We identified four major types of bias:

**Historical bias:** The training data accurately reflects an unequal world - **Representation bias:** Some groups are underrepresented or missing from the data - **Measurement bias:** The thing being measured is a poor proxy for the thing that matters - **Aggregation bias:** One-size-fits-all model